Apparatus and method for encoding an audio signal using a compensation value

ABSTRACT

An apparatus for encoding an audio signal includes: a core encoder for core encoding first audio data in a first spectral band; a parametric coder for parametrically coding second audio data in a second spectral band being different from the first spectral band, wherein the parametric coder includes: an analyzer for analyzing first audio data in the first spectral band to obtain a first analysis result and for analyzing second audio data in the second spectral band to obtain a second analysis result; a compensator for calculating a compensation value using the first analysis result and the second analysis result; and a parameter calculated for calculating a parameter from the second audio data in the second spectral band using the compensation value.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a continuation of copending U.S. application Ser.No. 16/283,668, filed Feb. 22, 2019, which is a continuation ofInternational Application No. PCT/EP2017/071048, filed Aug. 21, 2017,which is incorporated herein by reference in its entirety, andadditionally claims priority from European Application No. EP 16 185398.1, filed Aug. 23, 2016, which is incorporated herein by reference inits entirety.

TECHNICAL FIELD

The present invention is directed to audio coding and decoding, andspecifically to audio encoding/decoding using spectral enhancementtechnologies such as bandwidth extension or spectral band replication(SBR) or intelligent gap filling (IGF).

BACKGROUND OF THE INVENTION

Storage or transmission of audio signals is often subject to strictbitrate constraints. In the past, coders were forced to drasticallyreduce the transmitted audio bandwidth when only a very low bitrate wasavailable. Modern audio codecs are nowadays able to code wide-bandsignals by using bandwidth extension (BWE) methods [1-2]. Thesealgorithms rely on a parametric representation of the high-frequencycontent (HF)—which is generated from the waveform coded low-frequencypart (LF) of the decoded signal by means of transposition into the HFspectral region (“patching”) and application of a parameter driven postprocessing. However, if e.g. the spectral fine structure in a patchcopied to some target region is vastly different from the spectral finestructure of the original content, annoying artefacts might result anddegrade the perceptual quality of the decoded audio signal.

In BWE schemes, the reconstruction of the HF spectral region above agiven so-called cross-over frequency is often based on spectralpatching. Typically, the HF region is composed of multiple adjacentpatches and each of these patches is sourced from bandpass (BP) regionsof the LF spectrum below the given cross-over frequency.State-of-the-art systems efficiently perform the patching within afilterbank representation by copying a set of adjacent subbandcoefficients from a source to the target region. In a next step, thespectral envelope is adjusted such that it closely resembles theenvelope of the original HF signal that has been measured in the encoderand transmitted in the bitstream as side information.

However, often a mismatch in spectral fine structure exists that mightlead to the perception of artefacts. A commonly known mismatch isrelated to tonality. If the original HF includes a tone with ratherdominant energy content and the patch to be copied to the spectrallocation of the tone has a noisy characteristic, this bandpass noise canbe scaled up such that it becomes audible as an annoying noise burst.

Spectral band Replication (SBR) is a well-known BWE employed incontemporary audio codecs [1]. In SBR, the problem of tonality mismatchis addressed by insertion of artificial replacement sinusoids. However,this may involve additional side information to be transmitted to thedecoder enlarging the bit demand of BWE data. Moreover, inserted tonescan lead to instability over time if insertion of the tone toggleson/off for subsequent blocks.

Intelligent Gap Filling (IGF) denotes a semi-parametric coding techniquewithin modern codecs like MPEG-H 3D Audio or the 3gpp EVS codec. IGF canbe applied to fill spectral holes introduced by the quantization processin the encoder due to low-bitrate constraints. Typically, if the limitedbit budget does not allow for transparent coding, spectral holes emergein the high-frequency (HF) region of the signal first and increasinglyaffect the entire upper spectral range for lowest bitrates. At thedecoder side, such spectral holes are substituted via IGF usingsynthetic HF content generated in a semi-parametric fashion out oflow-frequency (LF) content, and post-processing controlled by additionalparametric side information.

As IGF is fundamentally based on filling the high frequency spectrum bycopying spectral parts (so-called tiles) from lower frequencies andadjusting the energies by applying a gain factor, it may proveproblematic if in the original signal the frequency range used as thesource of the copy-up process differs from its destination in terms ofspectral fine structure.

One such case that can have a strong perceptual impact is a differencein tonality. This tonality mismatch can occur in two different ways:either a frequency range with strong tonality is copied to a spectralregion that is supposed to be noise-like in structure, or the other wayaround with noise replacing a tonal component in the original signal. InIGF the former case—which is more common as most audio signals usuallybecome more noise-like toward higher frequencies—is handled by theapplication of spectral whitening where parameters are transmitted tothe decoder that signal how much whitening may be used, if any at all.For the latter case, tonality could be corrected by using the full bandencoding capability of the core coder to preserve tonal lines in the HFband through waveform coding. These so-called “surviving lines” could beselected based on strong tonality. Waveform coding is quite demanding interms of bitrate and in low bitrate scenarios it is most likely onecannot afford it. Moreover, toggling from frame to frame between codingand not coding a tonal component which would cause annoying artifactshas to be prevented.

The intelligent gap filling technology is additionally disclosed anddescribed in the European patent application EP 2830054 A1. The IGFtechnology addresses the problems related to the separation of bandwidthextension on the one hand and core decoding on the other hand byperforming the bandwidth extension in the same spectral domain in whichthe core decoder operates. Therefore, a full rate core encoder/decoderis provided, which encodes and decodes the full audio signal range. Thisdoes not require the need for a down sampler on the encoder side and anupsampler on the decoder side. Instead, the whole processing isperformed in the full sampling rate or full bandwidth domain. In orderto obtain a high coding gain, the audio signal is analyzed in order tofind the first set of first spectral portions which has to be encodedwith a high resolution, where this first set of first spectral portionsmay include, in an embodiment, tonal portions of the audio signal. Onthe other hand, non-tonal or noisy components in the audio signalconstituting a second set of second spectral portions are parametricallyencoded with low spectral resolution. The encoded audio signal then onlymay use the first set of first spectral portions encoded in thewaveform-preserving manner with a high spectral resolution, andadditionally the second set of second spectral portions encodedparametrically with a low resolution using frequency “tiles” sourcedfrom the first set. On the decoder side, the core decoder, which is afull band decoder, reconstructs the first set of first spectral portionsin a waveform-preserving manner, i.e. without any knowledge that thereis any additional frequency regeneration. However, the such generatedspectrum has a lot of spectral gaps. These gaps are subsequently filledwith the inventive intelligent gap filling (IGF) technology by using afrequency regeneration applying parametric data on the one hand andusing a source spectral range, i.e. first spectral portionsreconstructed by the full rate audio decoder on the other hand.

The IGF technology is also included and disclosed in 3GPP TS 26.445V13.2.0 (2016 June), Third Generation Partnership Project; TechnicalSpecification Group Services and System Aspect; Codec for Enhanced VoiceServices (EVS); Detailed Algorithmic Description (release 13). Inparticular, reference is made to section 5.3.3.2.11 “Intelligent GapFilling” of this reference regarding an encoder-side, and additionalreference is made to section 6 and in particular section 6.2.2.3.8 “IGFApply” and other IGF related passages, such as section 6.2.2.2.9 “IGFBitstream Reader” or section 6.2.2.3.11 “IGF Temporal Flattening” withrespect to the decoder-side implementation.

EP 2301027 B1 discloses an apparatus and a method for generatingbandwidth extension output data. In voiced speech signals, a lowering ofthe calculated noise floor yields a perceptually higher quality whencompared to the original calculated noise floor. As a result speechsounds less reverberant in this case. In case the audio signals comprisesibilants an artificial increase of the noise floor may cover updrawbacks in the patching method related to sibilants. Hence, thereference discloses providing a decrease of the noise floor for signalssuch as voiced speech and an increase of the noise floor for signalscomprising, e.g. sibilants. To distinguish the different signals,embodiments use energy distribution data (e.g. a sibilance parameter)that measures whether the energy is mostly located at higher frequenciesor higher frequency, or in other words whether the spectralrepresentation of the audio signal shows an increasing or decreasingtilt towards higher frequencies. Further implementations also use thefirst LPC coefficient (LPC equal to linear predictive coding) togenerate the sibilance parameter.

SUMMARY

According to an embodiment, an apparatus for encoding an audio signalmay have: a core encoder for core encoding first audio data in a firstspectral band; a parametric coder for parametrically coding second audiodata in a second spectral band being different from the first spectralband, wherein the parametric coder has: an analyzer for analyzing thefirst audio data in the first spectral band to obtain a first analysisresult and for analyzing the second audio data in the second spectralband to obtain a second analysis result; a compensator for calculating acompensation value using the first analysis result and the secondanalysis result; and a parameter calculator for calculating a parameterfrom the second audio data in the second spectral band using thecompensation value.

According to another embodiment, a method of encoding an audio signalmay have the steps of: core encoding first audio data in a firstspectral band; parametrically coding second audio data in a secondspectral band being different from the first spectral band, wherein theparametrically coding has: analyzing the first audio data in the firstspectral band to obtain a first analysis result and analyzing the secondaudio data in the second spectral band to obtain a second analysisresult; calculating a compensation value using the first analysis resultand the second analysis result; and calculating a parameter from thesecond audio data in the second spectral band using the compensationvalue, wherein the analyzing has calculating a tonal-to-noise ratio ofthe second audio data in the second spectral band, and wherein thecalculating the compensation value has calculating the compensationvalue dependent on the tonal-to-noise ratio of the second audio data sothat a first compensation value is obtained for a first tonal-to-noiseratio or a second compensation value is obtained for a secondtonal-to-noise ratio, the first compensation value being greater thanthe second compensation value, and the first tonal-to-noise ratio beinggreater than the second tonal-to-noise ratio.

According to another embodiment, a system for processing an audio signalmay have: an inventive apparatus for encoding an audio signal asmentioned above; and a decoder for receiving an encoded audio signalhaving encoded first audio data in the first spectral band and aparameter representing second audio data in the second spectral band,wherein the decoder is configured for performing a spectral enhancementoperation in order to regenerate synthesized audio data for the secondspectral band using the parameter and decoded first audio data in thefirst spectral band.

According to another embodiment, a method of processing an audio signalmay have the steps of: encoding an audio signal in accordance with theinventive method of encoding an audio signal as mentioned above; andreceiving an encoded audio signal having encoded first audio data in thefirst spectral band and a parameter representing second audio data inthe second spectral band; and performing a spectral enhancementoperation in order to regenerate synthesized audio data for the secondspectral band using the parameter and decoded first audio data in thefirst spectral band.

Still another embodiment may have a non-transitory digital storagemedium having computer-readable code stored thereon to perform a methodof encoding an audio signal, having: core encoding first audio data in afirst spectral band; parametrically coding second audio data in a secondspectral band being different from the first spectral band, wherein theparametrically coding has: analyzing the first audio data in the firstspectral band to obtain a first analysis result and analyzing the secondaudio data in the second spectral band to obtain a second analysisresult; calculating a compensation value using the first analysis resultand the second analysis result; and calculating a parameter from thesecond audio data in the second spectral band using the compensationvalue, wherein the analyzing has calculating a tonal-to-noise ratio ofthe second audio data in the second spectral band, and wherein thecalculating the compensation value has calculating the compensationvalue dependent on the tonal-to-noise ratio of the second audio data sothat a first compensation value is obtained for a first tonal-to-noiseratio or a second compensation value is obtained for a secondtonal-to-noise ratio, the first compensation value being greater thanthe second compensation value, and the first tonal-to-noise ratio beinggreater than the second tonal-to-noise ratio, when the computer-readablecode is run by a computer.

Another embodiment may have a non-transitory digital storage mediumhaving computer-readable code stored thereon to perform a method ofprocessing an audio signal, having: encoding an audio signal, having:core encoding first audio data in a first spectral band; parametricallycoding second audio data in a second spectral band being different fromthe first spectral band, wherein the parametrically coding has:analyzing the first audio data in the first spectral band to obtain afirst analysis result and analyzing the second audio data in the secondspectral band to obtain a second analysis result; calculating acompensation value using the first analysis result and the secondanalysis result; and calculating a parameter from the second audio datain the second spectral band using the compensation value, wherein theanalyzing has calculating a tonal-to-noise ratio of the second audiodata in the second spectral band, and wherein the calculating thecompensation value has calculating the compensation value dependent onthe tonal-to-noise ratio of the second audio data so that a firstcompensation value is obtained for a first tonal-to-noise ratio or asecond compensation value is obtained for a second tonal-to-noise ratio,the first compensation value being greater than the second compensationvalue, and the first tonal-to-noise ratio being greater than the secondtonal-to-noise ratio; receiving an encoded audio signal having encodedfirst audio data in the first spectral band and a parameter representingsecond audio data in the second spectral band; and performing a spectralenhancement operation in order to regenerate synthesized audio data forthe second spectral band using the parameter and decoded first audiodata in the first spectral band, when the computer-readable code is runby a computer.

An apparatus for encoding an audio signal comprises a core encoder forcore encoding first audio data in a first spectral band and a parametriccoder for parametrically coding second audio data in a second spectralband being different from the first spectral band. In particular, theparametric coder comprises an analyzer for analyzing first audio data inthe first spectral band to obtain a first analysis result and foranalyzing second audio data in the second spectral band to obtain asecond analysis result. A compensator calculates a compensation valueusing the first analysis result and the second analysis result.Furthermore, a parameter calculator then calculates a parameter from thesecond audio data in the second spectral band using the compensationvalue as determined by the compensator.

Thus, the present invention is based on the finding that in order tofind out whether a reconstruction using a certain parameter on thedecoder side addresses a certain characteristic that may be used by theaudio signal, the first spectral band, which is typically the sourceband, is analyzed to obtain the first analysis result. Analogously, thesecond spectral band, which is typically the target band, and which isreconstructed on the decoder-side using the first spectral band, i.e.the source band, is additionally analyzed by the analyzer to obtain thesecond analysis result. Thus, for the source band as well as the targetband, a separate analysis result is calculated.

Then, based on these two analysis results, a compensator calculates acompensation value for changing a certain parameter which would havebeen obtained without any compensation to a modified value. In otherwords, the present invention departs from the typical procedure, inwhich a parameter for the second spectral band is calculated from theoriginal audio signal and is transmitted to the decoder so that thesecond spectral band is reconstructed using the calculated parameter,and instead results in a compensated parameter calculated from thetarget band on the one hand and the compensation value which depends onboth the first and the second analysis results on the other hand.

The compensated parameter can be calculated by firstly calculating thenon-compensated parameter and then this non-compensated parameter can becombined with the compensation value to obtain the compensatedparameter, or the compensated parameter can be calculated in one shot,without the uncompensated parameter as an intermediate result. Thecompensated parameter can then be transmitted from the encoder to thedecoder, and then the decoder applies a certain bandwidth enhancementtechnology such as spectral band replication or intelligent gap fillingor any other procedure using the compensated parameter value. Thus, thestrong obedience to a certain parameter calculation algorithmirrespective of whether the parameter results in a desired spectral bandenhancement result is flexibly overcome by performing, in addition tothe parameter calculation, the signal analysis in the source band andthe target band and the subsequent calculation of a compensation valuebased on the result from the source band and the result from the targetband, i.e. from the first spectral band and the second spectral band,respectively.

Advantageously, the analyzer and/or the compensator apply a kind ofpsychoacoustic model determining a psychoacoustic mismatch. Hence, in anembodiment, the calculation of the compensation value is based on thedetection of a psychoacoustic mismatch of certain signal parameters suchas tonality and a compensation strategy is applied to minimize overallperceptual annoyance through modification of other signal parameterssuch as spectral band gain factors. Thus, by trading off different typesof artifacts, a perceptually well-balanced result is obtained.

As opposed to prior-art approaches “that try to fix tonality at anycost”, embodiments teach to rather remedy artefacts through applicationof a damping of problematic parts of the spectrum where a tonalitymismatch is detected, thereby trading off a spectral energy envelopemismatch against a tonality mismatch.

On input of several signal parameters, the compensation strategycontaining a perceptual annoyance model can decide on a strategy forobtaining a best perceptual fit rather than a mere signal parameter fit.

The strategy consists of weighing the perceptual significance ofpotential artefacts and choosing a parameter combination to minimize theoverall impairment.

This approach is mainly intended to be applied within a BWE based on atransform like the MDCT. Nevertheless, the teachings of the inventionare generally applicable, e.g. analogously within a Quadrature MirrorFilter bank (QMF) based system.

One possible scenario in which this technique may be applied is thedetection and subsequent damping of noise bands in the context ofIntelligent Gap Filling (IGF).

Embodiments handle a possible tonality mismatch through detecting itsoccurrence and reducing its effect by attenuating the correspondingscaling factor. This may on one hand lead to a deviation from theoriginal's spectral energy envelope, but on the other hand to areduction of HF noisiness which contributes to an overall increase inperceptual quality.

Thus, embodiments improve the perceptual quality through a novelparametric compensation technique, typically steered by a perceptualannoyance model, particularly in cases where, for example, a mismatch inspectral fine structure between the source or first spectral band andthe target or second spectral band exists.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the present invention will be detailed subsequentlyreferring to the appended drawings, in which:

FIG. 1 illustrates a block diagram of an apparatus for encoding an audiosignal in accordance with an embodiment;

FIG. 2 illustrates a block diagram of an apparatus for encoding with afocus on the compensation detector;

FIG. 3 a illustrates a schematic representation of an audio spectrumhaving a source range and an IGF or bandwidth extension range and anassociated mapping between source and destination bands;

FIG. 3 b illustrates a spectrum of an audio signal where the coreencoder applies IGF technology and where there are surviving lines inthe second spectral band;

FIG. 3 c illustrates a representation of a simulated first audio data inthe first spectral band to be used for the calculation of the firstanalysis result;

FIG. 4 illustrates a more detailed representation of the compensator;

FIG. 5 illustrates a more detailed representation of the parametercalculator;

FIG. 6 illustrates a flowchart for illustrating the compensationdetector functionality in an embodiment;

FIG. 7 illustrates a functionality of the parameter calculator forcalculating a non-compensated gain factor;

FIG. 8 a illustrates an encoder implementation having a core decoder forcalculating the first analysis result from an encoded and decoded firstspectral band;

FIG. 8 b illustrates a block diagram of an encoder in an embodiment, inwhich a patch simulator is applied for generating a first spectralbandwidth line shifted from the second spectral band to obtain the firstanalysis result;

FIG. 9 illustrates an effect of a tonality mismatch in an intelligentgap filling implementation;

FIG. 10 illustrates, in an embodiment, the implementation of theparametric encoder; and

FIGS. 11 a-11 c illustrate listening test results obtained from encodingaudio data using compensated parameter values.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 illustrates an apparatus for encoding an audio signal 100 in anembodiment of the present invention. The apparatus comprises a coreencoder 110 and a parametric coder 120. Furthermore, the core encoder110 and the parametric coder 120 are connected, on their input-side, toa spectral analyzer 130 and are connected, at their output side, to anoutput interface 140. The output interface 140 generates an encodedaudio signal 150. The output interface 140 receives, on the one hand, anencoded core signal 160 and at least a parameter for the second spectralband and typically a full parameter representation comprising theparameter for a second spectral band at input line 170. Furthermore, thespectral analyzer 130 separates the audio signal 100 into a firstspectral band 180 and a second spectral band 190. In particular, theparameter calculator comprises an analyzer 121 which is illustrated as asignal analyzer in FIG. 1 for analyzing first audio data in the firstspectral band 180 to obtain a first analysis result 122 and foranalyzing second audio data in the second spectral band 190 forobtaining a second analysis result 123. Both the first analysis result122 and the second analysis result 123 are provided to a compensator 124for calculating a compensation value 125. Thus, the compensator 124 isconfigured for using the first analysis result 122 and the secondanalysis result 123 for calculating the compensation value. Then, thecompensation value 125 on the one hand and at least the second audiodata from the second spectral band 190 (the first spectral data from thefirst spectral band may be used as well) are both provided to aparameter calculator 126 for calculating a parameter 170 from the secondaudio data in the second spectral band using the compensation value 125.

The spectral analyzer 130 in FIG. 1 can be, for example, astraightforward time/frequency converter to obtain individual spectralbands or MDCT lines. In this implementation, therefore, the spectralanalyzer 130 implements a modified discrete cosine transform (MDCT) toobtain spectral data. Then, this spectral data is further analyzed inorder to separate data for the core encoder 110 on the one hand and datafor the parametric coder 120 on the other hand. Data for the coreencoder 110 at least comprise the first spectral band. Furthermore, thecore data may additionally comprise further source data when the coreencoder is to encode more than one source band.

Thus, the core encoder may receive, as input data to be core encoded,the whole bandwidth below a cross-over frequency in the case of spectralband replication technologies, while the parametric coder then receivesall audio data above this cross-over frequency.

In the case of an intelligent gap filling framework, however, the coreencoder 110 may additionally receive spectral lines above an IGF startfrequency which are also analyzed by the spectral analyzer 130 so thatthe spectral analyzer 130 additionally determines data even above theIGF start frequency where this data above the IGF start frequency isadditionally encoded by the core encoder. To this end, the spectralanalyzer 130 may also be implemented as a “tonal mask” which is, forexample, also discussed in section 5.3.3.2.11.5 “IGF Tonal Mask” asdisclosed in 3GPP TS 26.445 V13.0.0(12). Thus, in order to determinewhich spectral component should be transmitted with the core encoder,the tonal mask is calculated by the spectral analyzer 130. Therefore,all significant spectral content is identified, whereas content that iswell-suited for parametric coding through IGF is quantized to zero bythe tonal mask. The spectral analyzer 130 nevertheless forwards thespectral content that is well-suited for parametric coding to theparametric coder 120, and this data may for example be the data that hasbeen set to zero by the tonal mask processing.

In an embodiment, illustrated in FIG. 2 , the parametric coder 120 isadditionally configured for parametrically coding third audio data in athird spectral band to obtain a further parameter 200 for this thirdspectral band. In this case, the analyzer 121 is configured foranalyzing the third audio data in the third spectral band 202 to obtaina third analysis result 204 in addition to the first analysis result 122and the second analysis result 123.

Furthermore, the parametric coder 120 from FIG. 1 additionally comprisesa compensation detector 210 for detecting, using at least the thirdanalysis result 204, whether the third spectral band is to becompensated or not. The result of this detection is output by a controlline 212 which either indicates a compensation situation for the thirdspectral band or not. The parameter calculator 126 is configured tocalculate the further parameter 200 for the third spectral band withoutany compensation value, when the compensation detector detects the thirdspectral band is not to be compensated as provided by the control line212. However, if the compensation detector detects that the thirdspectral band is to be compensated, then the parameter calculator isconfigured to calculate the further parameter 200 for the third spectralband with an additional compensation value calculated by the compensator124 from the third analysis result 200.

In an embodiment, where a quantitative compensation is applied, theanalyzer 121 is configured to calculate, as the first analysis result, afirst quantitative value 122 and as the second analysis result a secondquantitative value 123. Then, the compensator 124 is configured tocalculate a quantitative compensation value 125 from the firstquantitative value and from the second quantitative value. Finally, theparameter calculator is configured for calculating the quantitativeparameter using the quantitative compensation value.

However, the present invention is also applicable when only qualitativeanalysis results are obtained. In this situation, a qualitativecompensation value is calculated which then controls the parametercalculator to lower or increase a certain non-compensated parameter by acertain degree. Thus, both analysis results together may result in acertain increase or decrease of a parameter, the certain increase ordecrease is fixed and is therefore not dependent on any quantitativeresult. However, quantitative results may be used over a fixedincrease/decrease increments, although the latter calculations are lesscomputationally intensive.

Advantageously, the signal analyzer 121 analyzes a first characteristicof the audio data to obtain the first analysis result and additionallyanalyzes the same first characteristic of the second audio data in thesecond spectral band to obtain the second analysis result. Contrarythereto, the parameter calculator is configured for calculating theparameter from the second audio data in the second spectral band byevaluating a second characteristic where this second characteristic isdifferent from this first characteristic.

Exemplarily, FIG. 2 illustrates the situation where the firstcharacteristic is a spectral fine structure or an energy distributionwithin a certain band such as the first, the second or any other band.Contrary thereto, the second characteristic applied by the parametercalculator or determined by the parameter calculator is a spectralenvelope measure, an energy measure or a power measure or generally anamplitude-related measure giving an absolute or relative measure of thepower/energy in a band such as, for example, a gain factor. However,other parameters which measure a different characteristic from a gainfactor characteristic can be calculated by the parameter calculator aswell. Furthermore, other characteristics for the individual source bandon the one hand and the destination band on the other hand, i.e. thefirst spectral band and the second spectral band respectively, can beapplied and analyzed by the analyzer 121.

Furthermore, the analyzer 121 is configured to calculate the firstanalysis result 122 without using the second audio data in the secondspectral band 190 and to additionally calculate the second analysisresult 123 without using the first audio data in the first spectral band180 where, in this embodiment, the first spectral band and the secondspectral band are mutually exclusive to each other, i.e. do not overlapwith each other.

Furthermore, the spectral analyzer 130 is additionally configured tobuild frames of the audio signal or to window an incoming stream ofaudio samples to obtain frames of audio samples, where the audio samplesin neighboring frames are overlapping with each other. In case of a 50%overlap, for example, a second portion of an earlier frame has audiosamples that are derived from the same original audio samples includedin the first half of the subsequent frame, where the audio sampleswithin a frame are derived from the original audio samples by windowing.

In this case, when the audio signal comprises a time sequence of framesas, for example, additionally provided by the block 130 of FIG. 1additionally having a frame builder functionality, the compensator 124is configured to calculate a current compensation value for a currentframe using a previous compensation frame value for a previous frame.This typically results in a kind of a smoothing operation.

As outlined later on, the compensation detector 210 illustrated in FIG.2 may additionally or alternatively from other features in FIG. 2comprise a power spectrum input and a transient input illustrated at221, 223, respectively.

In particular, the compensation detector 210 is configured to onlyinstruct a compensation to be used by the parameter calculator 126, whena power spectrum of the original audio signal 100 of FIG. 1 isavailable. This fact, i.e. whether or not the power spectrum isavailable, is signaled by a certain data element or flag.

Furthermore, the compensation detector 210 is configured to only allow acompensation operation via the control line 212, when a transientinformation line 223 signals that, for the current frame, a transient isnot present. Thus, when line 223 signals that a transient is present,the whole compensation operation is disabled irrespective of anyanalysis results. This of course applies for the third spectral band,when a compensation has been signaled for the second spectral band.However, this also applies for the second spectral band in a certainframe, when for this frame a situation such as a transient situation isdetected. Then, the situation can occur and will occur that, for acertain time frame, any parameter compensation does not take place atall.

FIG. 3 a illustrates a representation of a spectrum of amplitudes A(f)or squared amplitudes A²(f). In particular, an XOVER or IGF startfrequency is illustrated.

Furthermore, a set of overlapping source bands are illustrated, wherethe source bands comprise the first spectral band 180, a further sourceband 302 and an even further source band 303. Additionally, destinationbands above the IGF or XOVER frequency are the second spectral band 190,a further destination band 305, an even further destination band 307 andthe third spectral band 202, for example.

Typically, mapping functions within the IGF or bandwidth extensionframework define a mapping between the individual source bands 180, 302,303 and the individual destination bands 305, 190, 307, 202. Thismapping may be fixed as it is the case in 3GPP TS 26.445 or can beadaptively determined by a certain IGF encoder algorithm. In any case,FIG. 3 a illustrates, in the lower table, the mapping between adestination band and the source band for the case of non-overlappingdestination bands and overlapping source bands irrespective of whetherthis mapping is fixed or is adaptively determined and actually has beenadaptively determined for a certain frame, the spectrum beingillustrated in the upper portion of FIG. 3 a.

FIG. 4 illustrates a more detailed implementation of the compensator124. The compensator 124 receives, in this implementation, in additionto the first analysis result 122, which can be a spectral flatnessmeasure, a crest factor, a spectral tilt value or any other kind ofparametric data for the first spectral band, an analysis result 123 forthe second spectral band. This analysis result may, once again, be aspectral flatness measure for the second spectral band, a crest factorfor the second spectral band or a tilt value, i.e. a spectral tilt valuelimited to the second spectral band while the tilt value or spectraltilt value for the first spectral band is also limited for the firstspectral band. Additionally, the compensator 124 receives a spectralinformation on the second spectral band such a stop line of the secondspectral band. Thus, in the situation where the parametric calculator126 of FIG. 2 is configured for parametrically coding third audio datain the third spectral band 202, the third spectral band comprises higherfrequencies than the second spectral band. This is also illustrated inthe example of FIG. 3 a , where the third spectral band is at higherfrequencies than the second spectral band, i.e. where band 202 hashigher frequencies than band 190. In this situation, the compensator 124is configured to use a weighting value in calculating the compensationvalue for the third spectral band, where this third weighting value isdifferent for a weighting value used for calculating the compensationvalue for the second spectral band. Thus, in general, the compensator124 influences the calculation of the compensation value 125 so that,for the same other input values, the compensation value is smaller forhigher frequencies.

The weighting value can, for example, be an exponent applied in thecalculation of the compensation value based on the first and the secondanalysis results such as the exponent a, as described later on, or can,for example, be a multiplicative value or even a value to be added orsubtracted so that a different influence for higher frequencies isobtained compared to the influence when the parameter is to becalculated for lower frequencies.

Additionally, as illustrated in FIG. 4 , the compensator receives atonal-to-noise ratio for the second spectral band in order to calculatethe compensation value dependent on the tonal-to-noise ratio of thesecond audio data in the second spectral band. Thus, a firstcompensation value is obtained for a first tonal-to-noise ratio or asecond compensation value is obtained for a second tonal-to-noise ratio,where the first compensation value is greater than the secondcompensation value when the first tonal-to-noise ratio is greater thanthe second tonal-to-noise ratio.

As stated, the compensator 124 is configured to generally determine thecompensation value by applying a psychoacoustic model, wherein thepsychoacoustic model is configured to evaluate the psychoacousticmismatch between the first audio data and the second audio data usingthe first analysis result and the second analysis result to obtain thecompensation value. This psychoacoustic model evaluating thepsychoacoustic mismatch can be implemented as a feedforward calculationas discussed later on in the context of the following SFM calculationsor can, alternatively be a feedback calculation module applying a kindof an analysis by synthesis procedure. Furthermore, the psychoacousticmodel may also be implemented as a neural network or a similar structurethat is automatically drained by certain training data to decide inwhich case a compensation may be used and in which case not.

Subsequently, the functionality of the compensation detector 210illustrated in FIG. 2 or, generally, a detector included in theparameter calculator 120 is illustrated.

The compensation detector functionality is configured to detect acompensation situation when a difference between the first analysisresult and the second analysis result has a predetermined characteristicas illustrated, for example, at 600 and 602 in FIG. 6 . Block 600 isconfigured to calculate a difference between the first and the secondanalysis result and block 602 then determines whether the difference hasa predetermined characteristic or a predetermined value. If it isdetermined that the predetermined characteristic is not there, then itis determined by block 602 that no compensation is to be performed asillustrated at 603. If, however, it is determined that the predeterminedcharacteristic exists, then control proceeds via line 604. Furthermore,the detector is configured to alternatively or additionally determinewhether the second analysis result has a certain predetermined value ora certain predetermined characteristic. If it is determined that thecharacteristic does not exist, then line 605 signals that nocompensation is to be performed. If, however, it is determined that thepredetermined value is there, control proceeds via line 606. Inembodiments, lines 604 and 606 may be sufficient to determine whetherthere is a compensation or not. However, in the embodiment illustratedin FIG. 6 , further determinations based on the spectral tilt of thesecond audio data for the second spectral band 190 of FIG. 1 areperformed as described later on.

In an embodiment, the analyzer is configured to calculate a spectralflatness measure, a crest factor or a quotient of the spectral flatnessmeasure and the crest factor for the first spectral band as the firstanalysis result and to calculate a spectral flatness measure or a crestfactor or a quotient of the spectral flatness measure and the crestfactor of the second audio data as the second analysis result.

In such an embodiment, the parameter calculator 126 is additionallyconfigured to calculate, from the second audio data, a spectral envelopeinformation or a gain factor.

Furthermore, in such an embodiment, the compensator 124 is configured tocalculate the compensation value 125 so that, for a first differencebetween the first analysis result and the second analysis result, afirst compensation value is obtained, and for a difference between thefirst analysis result and the second analysis result, a secondcompensation value is calculated, where the first difference is greaterthan the second difference, when the first compensation value is greaterthan the second compensation value.

In the following, the description of FIG. 6 will be continued byillustrating the optional additional determination whether acompensation situation is to be detected or not.

In block 608, a spectral tilt is calculated from the second audio data.When it is determined that this spectral tilt is below a threshold asillustrated in 610, then a compensation situation is positively affirmedas illustrated at 612. When, however, it is determined that the spectraltilt is not below the predetermined threshold, but above the threshold,then this situation is signaled by line 614. In block 616, it isdetermined whether a tonal component is close to a border of the secondspectral band 190. When it is determined that there is a tonal componentclose to the border as illustrated by item 618, then a compensationsituation is once again positively affirmed. When, however, it isdetermined that no tonal component exists close to a border, then anycompensation is canceled, i.e., switched off as illustrated by line 620.The determination in block 616, i.e., the determination whether a tonalcomponent is close to a border or not is made by performing, in anyembodiment, a shifted SFM calculation. When there is a strong decline inthe slope as determined by block 608, then the frequency region, forwhich the SFM is calculated, will be shifted down by half the width ofthe corresponding scale factor band (SFB) or the second spectral band.For a strong incline, the frequency region, for which the SFM iscalculated is shifted up by half the width of the second spectral band.In this way, tonal components that are supposed to be damped can stillbe correctly detected due to a low SFM while for higher SFM values,damping will not be applied.

Subsequently, FIG. 5 is discussed in more detail. Particularly, theparameter calculator 126 may comprise the calculator 501 for calculatingthe non-compensated parameter from the audio data for the secondspectral band, i.e., the destination band, and the parameter calculator126 additionally comprises a combiner 503 for combining thenon-compensated parameter 502 and the compensation value 125. Thiscombination may, for example, be a multiplication, when thenon-compensated parameter 502 is a gain value and the compensation value105 is a quantitative compensation value. However, the combinationperformed by the combiner 503 can, alternatively, also be a weightingoperation using the compensation value as an exponent or an additivemodification where the compensation value is used as an additive orsubtractive value.

Furthermore, it is to be noted that the embodiment illustrated in FIG. 5, where the non-compensated parameter is calculated and, then, asubsequent combination with the combination value is performed, is onlyan embodiment. In alternative embodiments, the compensation value canalready be introduced into the calculation for the compensated parameterso that any intermediate result with an explicit non-compensatedparameter does not occur. Instead, only a single operation is performedwhere, as a result of this “single operation”, the compensated parameteris calculated using the compensation value and using a calculationalgorithm which would result in the non-compensated parameter, when thecompensation value 125 would not be introduced into such a calculation.

FIG. 7 illustrates a procedure to be applied by the calculator 501 forcalculating the non-compensated parameter. The representation in FIG. 7“IGF scale factor calculation” roughly corresponds to section5.3.3.2.11.4 of 3gpp TS 26.445 V13.3.3 (2015/12). When, a “complex” TCXpower spectrum P (a spectrum, where the real parts and the imaginaryparts of spectral lines are evaluated) is available, then the calculator501 for calculating the non-compensated parameter of FIG. 5 performs acalculation of an amplitude-related measure for the second spectral bandfrom the power spectrum P as illustrated at 700. Furthermore, thecalculator 501 performs a calculation of an amplitude-related measurefor the first spectral band from the complex spectrum P as illustratedat 702. Additionally, the calculator 501 performs a calculation of anamplitude-related measure from the real part of the first spectral band,i.e., the source band as illustrated at 704, so that threeamplitude-related measures E_(cplx, target), E_(cplx, source),E_(real, source) are obtained and input into a further gain factorcalculation functionality 706 to finally obtain a gain factor being afunction of the quotient between E_(real, source) and E_(cplx, source)multiplied by E_(cplx, target).

When, alternatively, the complex TCX power spectrum is not available,then the amplitude-related measure is only calculated from the realsecond spectral band as illustrated at the bottom of FIG. 7 .

Furthermore, it is to be noted that the TCX power spectrum P iscalculated, for example, as illustrated in subclause 5.3.3.2.11.1.2based on the following equation:

P(sb)=R ²(sb)+I ²(sb),sb=0,1,2, . . . ,n−1.

Here, n is the actual TCX window length, R is the vector containing thereal valued part (cos-transformed) of the current TCX spectrum, and I isthe vector containing the imaginary (sin-transformed) part of thecurrent TCX spectrum. Particularly, the term “TCX” is related to the3gpp terminology, but generally mentions the spectral values in thefirst spectral band or the second spectral band as provided by thespectral analyzer 130 to the core encoder 110 or the parametric coder120 of FIG. 1 .

FIG. 8 a illustrates an embodiment, where the signal analyzer 121further comprises a core decoder 800 for calculating an encoded andagain decoded first spectral band and for calculating, naturally, theaudio data in the encoded/decoded first spectral band.

Then, the core decoder 800 feeds the encoded/decoded first spectral bandinto an analysis result calculator 801 included in the signal analyzer821 to calculate the first analysis result 122. Furthermore, the signalanalyzer comprises a second analysis result calculator 802 included inthe signal analyzer 121 of FIG. 1 for calculating the calculated secondanalysis result 123. Thus, the signal analyzer 121 is configured in sucha way that the actual first analysis result 122 is calculated using theencoded and again decoded first spectral band while the second analysisresult is calculated from the original second spectral band. Thus, thesituation on the decoder-side is better simulated on the encoder-side,since the input into the analysis result calculator 801 already has allthe quantization errors included in the decoded first audio data for thefirst spectral band available at the decoder.

FIG. 8 b illustrates a further implementation of the signal analyzerthat has, either alternatively to the FIG. 8 a procedure, oradditionally to the FIG. 8 a procedure a patch simulator 804. The patchsimulator 804 specifically acknowledges the functionality of the IGFencoder, i.e., that there can be lines or at least one line within thesecond destination band which is actually encoded by the core encoder.

Particularly, this situation is illustrated in FIG. 3 b.

FIG. 3 b illustrates, similar to FIG. 3 a , upper portion, the firstspectral band 180 and the second spectral band 190. However, in additionto what has been discussed in FIG. 3 a , the second spectral bandcomprises specific lines 351, 352 included within the second spectralband that have been determined by the spectral analyzer 130 as linesthat are additionally encoded by the core encoder 110 in addition to thefirst spectral band 180.

This specific coding of certain lines above the IGF start frequency 310reflects the situation that the core encoder 110 is a full band encoderhaving a Nyquist frequency up to f_(max) 354 being higher than the IGFstart frequency. This is in contrast to SBR technology-relatedimplementations there the crossover frequency is also the maximumfrequency and, therefore, the Nyquist frequency of the core encoder 110.

The test simulator 804 receives either the first spectral band 180 orthe decoded first spectral band from the core decoder 800 and,additionally, information from the spectral analyzer 130 or the coreencoder 110 that there are actually lines in the second spectral bandthat are included in the core encoder output signal. This is signaled bythe spectral analyzer 130, via a line 806 or is signaled by the coreencoder via a line 808. The patch simulator 804 now simulates the firstaudio data for the first spectral band by using the straightforwardfirst audio data for the four spectral bands and by inserting the lines351, 352 from the second spectral band into the first spectral band byshifting these lines to the first spectral band. Thus, lines 351′ and352′ represent spectral lines obtained by shifting the lines 351, 352 ofFIG. 3 b from the second spectral band into the first spectral band.Advantageously, the spectral lines 351, 352 are generated in such a wayfor the first spectral band that the location of these lines within theband borders are identical in both bands, i.e., the difference frequencybetween a line and the band border is identical to the second spectralband 190 and the first spectral band 180.

Thus, the patch simulator outputs a simulated data 808 illustrated inFIG. 3 c having a straightforward first spectral band data and,additionally, having the lines shifted from the second spectral band tothe first spectral band. Now, the analysis result calculator 801calculates the first analysis result 102 using the specific data 808while the analysis result calculator 802 calculates the second analysisresult 123 from the original second audio data in the second spectralband, i.e., the original audio data including the lines 351, 352illustrated in FIG. 3 b.

This procedure with the patch simulator 804 has the advantage that it isnot necessary to put certain conditions on the additional lines 351,352, such as high tonality or anything else. Instead, it is totally upto the spectral analyzer 130 or the core encoder 110 to decide whethercertain lines in the second spectral band are to be encoded by the coreencoder. The result of this operation, however, is automaticallyaccounted for by using these lines as an additional input for thecalculation of the first analysis result 122 as illustrated in FIG. 8 b.

Subsequently, the effect of a tonality mismatch within an intelligentgap filling framework is illustrated.

In order to detect noise band artifacts the difference in tonalitybetween the source and target scale factor bands (SFBs) has to bedetermined. For tonality calculation the spectral flatness measure (SFM)can be used. If a tonality mismatch—where the source band is muchnoisier than the target band—is found, a certain amount of dampingshould be applied. This situation is depicted in FIG. 9 without theinventive processing applied.

It is also sensible to apply some smoothing to damping factors in orderto avoid an abrupt on-/off behavior of the tool. A detailed descriptionof the steps to apply damping in the right places is given in thefollowing. (Note that damping will only be applied if both the TCX powerspectrum P is available and the frame is non-transient (flag isTransient inactive).)

Tonality Mismatch Detection: Parameters

In a first step, those SFBs, where a tonality mismatch might cause noiseband artefacts, have to be identified. In order to do so the tonality ineach SFB of the IGF range and the corresponding bands that are used forcopy-up has to be determined. One suitable measure for calculatingtonality is the spectral flatness measure (SFM) which is based on adivision of the geometric mean of a spectrum by its arithmetic mean andranges between 0 and 1. Values close to 0 indicate strong tonality whilea value approaching 1 is a sign of a very noisy spectrum. The formula isgiven as

${{sfm}\left( {P,b,e} \right)} = {2^{({\frac{1}{2} + p})}\left( {\frac{1}{e - b}\left( {1 + {\sum\limits_{{sb} = b}^{e - 1}{P\left( {sb} \right)}}} \right)} \right)^{- 1}}$

where P is the TCX power spectrum, b the start line and e the stop lineof the current SFB while p is defined as

$p = {\frac{1}{e - b}{\overset{e - 1}{\sum\limits_{{sb} = b}}\left\lfloor {\max\left( {0,{\log_{2}\left( {P({sb})} \right)}} \right)} \right\rfloor}}$

Additionally to the SFM, the crest factor is calculated which also givesan indication of how the energy is distributed inside a spectrum bydividing the maximum energy by the mean energy of all the frequency binsin the spectrum. Dividing the SFM by the crest factor results in atonality measure of an SFB for the current frame. The crest factor iscalculated by

${{crest}\left( {P,b,e} \right)} = {\max\left( {1,{E_{\max}\left( {\frac{1}{e - b}{\overset{e - 1}{\sum\limits_{{sb} = b}}\left\lfloor {\max\left( {0,{\log_{2}\left( {P({sb})} \right)}} \right)} \right\rfloor^{2}}} \right)}^{- \frac{1}{2}}} \right)}$

where P is the TCX power spectrum, b the start line and e the stop lineof the current SFB while E_(max) is defined as

$E_{\max} = \left\lfloor {\max\limits_{{sb} \in {\lbrack{b,{e\lbrack{\subset N}}}}}\left( {0,{\log_{2}\left( {P({sb})} \right)}} \right)} \right\rfloor$

It is, however, sensible to also use results from previous frames toachieve a smooth tonality estimation. Thus, the tonality estimation isdone with the following formula:

${{SFM} = {\min\left( {{2.7},{\frac{sfm}{crest} + \frac{{sfm}_{prev}}{crest_{prev}} + {{0.5}*{SFM}_{prev}}}} \right)}},$

where sfm denotes the result of the actual spectral flatnesscalculation, while the variable SFM includes the division by the crestfactor as well as smoothing.

Now the difference in tonality between source and destination iscalculated:

SFM_(diff)=SFM_(src)−SFM_(dest)

For positive values of this difference the condition that something thatis noisier than the target spectrum is used for copy-up is fulfilled.Such an SFB becomes a likely candidate for damping.

However, a low SFM value does not necessarily indicate strong tonalitybut can also be due to a sudden decline or incline of the energy in anSFB. This particularly applies to items where there is band-limitationsomewhere in the middle of an SFB. This can lead to unwanted dampingcreating the impression of a slightly low-pass filtered signal.

In order to avoid damping in such cases, possibly affected SFBs aredetermined by calculating the spectral tilt of the energy in all bandswith positive SFM_(diff), where a strong tilt in one direction mightindicate a sudden drop that causes a low SFM value. The spectral tilt iscalculated as a linear regression through all spectral bins in the SFB,with the slope of the regression line given by the following formula:

${{slope} = {\left( {{\sum\limits_{i}{x_{i}P_{i}}} - {\frac{1}{e - b}{\sum\limits_{i}{x_{i}{\sum\limits_{i}P_{i}}}}}} \right)\left( {{\sum\limits_{i}x_{i}^{2}} - {\frac{1}{e - b}\left( {\sum\limits_{i}x_{i}} \right)^{2}}} \right)^{- 1}}},{i = b},{\ldots.},{e - 1}$

with x as the bin number, P the TCX power spectrum, b the start line ande the stop line of the current SFB.

However, a tonal component close to a border of an SFB might also causea steep tilt, but should still be subjected to damping. To separatethese two cases, another shifted SFM calculation should be performed forbands with steep tilt.

The threshold for the slope value is defined as

${thresh}_{tilt} = \frac{60}{e - b}$

with division by the SFB width as normalization.

If there is a strong decline slope <−thresh_(tilt), the frequency regionfor which SFM is calculated will be shifted down by half the width ofthe SFB; for a strong incline slope >thresh_(tilt) it is shifted up. Inthis way, tonal components that are supposed to be damped can still becorrectly detected due to low SFM while for higher SFM values dampingwill not be applied. The threshold here is defined as the value 0.04,where damping is only applied if the shifted SFM falls below thethreshold.

Perceptual Annoyance Model

Damping should not be applied for any positive SFM_(diff), but onlymakes sense if the target SFB is indeed very tonal. If in a specific SFBthe original signal is superimposed by a noisy background signal, thenthe perceptual difference to an even noisier band will be small and thedullness due to loss of energy by damping may outweigh the benefits.

To ensure application within reasonable bounds damping should only beused if the target SFB is indeed very tonal. So only whenever both

SFM_(diff)>0

and

SFM_(dest)<0.1

hold, damping should be applied.

Another matter that should be considered is the background of tonalcomponents in the IGF spectrum. The perceptual degradation caused bynoise-band artefacts is likely to be most apparent whenever there islittle to no noise-like background surrounding the original tonalcomponent. In this case, when comparing the original with theIGF-created HF spectrum, an introduced noise band will be perceived assomething entirely new and thus stick out very prominently. If, on theother hand, there already is a considerable amount of background noiseexistent, then the additional noise blends in with the backgroundresulting in a less jarring perceptual difference. Thus, the amount ofapplied damping should also depend on the tonal-to-noise ratio in theaffected SFB.

For the calculation of this tonal-to-noise ratio the squared TCX powerspectral values P of all bins i in an SFB are summed up and divided bythe width of the SFB (given by start line b and stop line e) to get theaverage energy of the band. This average is subsequently used tonormalize all the energies in the band.

${P_{{norm},k} = {\sqrt{P_{k}}\left( {\frac{1}{e - b}*{\sum\limits_{{sb} = b}^{e - 1}\sqrt{P_{sb}}}} \right)^{- 1}}},{k = b},\ldots,{e - 1}$

All bins with a normalized energy P_(norm,k) below 1 are then summed upand counted as the noise part P_(noise) while everything above athreshold of 1+adap with

${adap} = \frac{e - b}{40}$

is counted as the tonal part P_(tonal). This threshold is dependent onthe width of the SFB so that smaller bands get a lower threshold toaccount for the higher average due to the bigger influence of thehigh-energy bins of the tonal component. From the tonal and the noisepart finally a log-ratio is computed.

${tonalToNoise}{= {20*{\log_{10}\left( \frac{P_{tonal}}{P_{noise}} \right)}}}$

Damping depends on both the difference in SFM between source anddestination and the SFM of the target SFB where higher differences and asmaller target SFM should both lead to stronger damping. It isreasonable that for a bigger difference in tonality a stronger dampingshould be applied. Furthermore, the amount of damping should alsoincrease more quickly if the target SFM is lower, i.e. the target SFBmore tonal. This means that for extremely tonal SFBs a stronger dampingwill be applied than for SFBs where the SFM falls just within thedamping range.

Additionally, damping should also be applied more sparingly for higherfrequencies as taking away the energy in the highest bands might easilylead to the perceptual impression of band-limitation while the finestructure of the SFBs becomes less important due to decreasingsensitivity of the human auditory system towards higher frequencies.

Tonality Mismatch Compensation: Calculation of Damping Factor

To incorporate all these considerations into a single damping formulathe ratio between the target and the source SFM is taken as the basis ofthe formula. In this way both a bigger absolute difference in SFM and asmaller target SFM value will lead to stronger damping which makes itmore suitable than simply taking the difference. To also adddependencies on frequency and tonal-to-noise ratio adjustment parametersare applied to this ratio. Thus, the damping formula can be written as

${d_{curr} = {\left( \frac{SFM_{dest}}{SFM_{src}} \right)^{\alpha} + \beta}},$

where d is the damping factor that will be multiplied with the scalingfactor and α and β the damping adjustment parameters that are calculatedas

$\alpha = {\min\left( {\frac{320}{e - 1},{{1.2}5}} \right)}$

where e is the stop line of the current SFB and

$\beta = \left\{ \begin{matrix}{{0.1*\left( {\left( {10 + {adap}} \right) - {tonalToNoise}} \right)},} & {{{if}\left( {\left( {10 + {adap}} \right) - {tonalToNoise}} \right)} > 0} \\{0,} & {else}\end{matrix} \right.$

where adap is dependent on the SFB width calculated by

${adap} = \frac{width}{40}$

The parameter a decreases with frequency in order to apply less dampingfor higher frequencies while β is used to further reduce the strength ofthe damping if the tonal-to-noise ratio of the SFB that is to be dampedfalls below a threshold. The more significantly it falls below thisthreshold, the more the damping is reduced.

As damping is only activated within certain constraints, smoothing maybe applied in order to prevent abrupt on/off transitions. To realizethis, several smoothing mechanisms are active.

Directly after a transient, a core switch to TCX or an undamped previousframe damping is only gradually applied with full force to avoid extremeenergy drops after high-energy transients. Furthermore, a forgettingfactor in the form of an IIR filter is utilized to also take the resultsof previous frames into account.

All smoothing techniques are comprised in the following formula:

${d = {\min\left( {{\frac{d_{curr} + d_{prev}}{2} + {0.1*{smooth}}},1} \right)}},$

where d_(prev) is the damping factor of the previous frame. If dampingwas not active in the previous frame d_(prev) is overwritten withd_(curr) but limited to a minimum of 0.1. The variable smooth is anadditional smoothing factor that will be set to 2 during transientframes (flag isTransient active) or after core switches (flagisCelpToTCX active), to 1 if in the previous frame damping was inactive.In each frame with damping the variable will be decreased by 1, but maynot fall below 0.

In the final step, the damping factor d is multiplied with the scalinggain g:

g _(damped) =g*d

FIG. 10 illustrates an implementation of the present invention.

The audio signal as, for example, output by the spectral analyzer 130 isavailable as an MDCT spectrum or even a complex spectrum as indicated by(c) to the left of FIG. 10 .

The signal analyzer 121 is implemented by the tonality detectors 801 and802 in FIG. 10 for detecting the tonality of the target content by block802 and for detecting the tonality of the (simulated) source content atitem 801.

Then, the damping factor calculation 124 is performed to obtain thecompensation value and, then, the compensator 503 operates using thedata obtained from item 501, 700-706. Item 501 and item 700-706 reflectthe envelope estimation from the target content and the envelopeestimation from the simulated source content and the subsequent scalingfactor calculation as, for example, illustrated in FIG. 7 at item700-706.

Thus, the non-compensated scaling vector is input into block 503 asvalue 502 in analogy to what has been discussed in the context of FIG. 5. Furthermore, a noise model 1000 is illustrated in FIG. 10 as aseparate building block, although same can also be directly includedwithin the damping factor calculator 124 as has been discussed in thecontext of FIG. 4 .

Furthermore, the parametric IGF encoder in FIG. 10 additionallycomprising a whitening estimator is configured for calculating whiteninglevels as discussed, for example, in item 5.3.3.2.11.6.4 “Coding of IGFwhitening levels”. Particularly, IGF whitening levels are calculated andtransmitted using one or two bits per tile. This data is introduced intothe bitstream multiplexer 140 as well in order to finally obtain thecomplete IGF parametric data.

Furthermore, block “sparsify spectrum” that may correspond to block 130with respect to the determination of spectral lines to be encoded by thecore encoder 110 is additionally provided and is illustrated as aseparate block 1020 in FIG. 10 . This information may be used by thecompensator 503 in order to reflect the specific IGF situation.

Furthermore, the term “simulated” to the left of block 801 and the“envelope estimation” block in FIG. 10 refers to the situationillustrated in FIG. 8 a , where the “simulated source content” is thecoded and again decoded audio data in the first spectral band.

Alternatively, the “simulated” source content is the data obtained bythe patch simulator 804 from the original first audio data in the firstspectral band as indicated by line 180 or is the decoded first spectralband as obtained by the core decoder 800 enriched with the lines shiftedfrom the second spectral band to the first spectral band.

Subsequently, a further embodiment of the invention constituting anamended version of a 3gpp TS 26.445 codec is illustrated. Newly addedtext specifying the inventive processing is provided in the following.Herein, explicit reference is made to certain subclauses alreadycontained in the 3gpp TS 26.445 specification.

5.3.3.2.11.1.9 The Spectral Tilt Function SLOPE

Let P∈P^(n) be the TCX power spectrum as calculated according tosubclause 5.3.3.2.11.1.2 and b the start line and e the stop line of thespectral tilt measurement range.

The SLOPE function, applied with IGF, is defined with:

${{SLOPE}:\left. {P^{n} \times N \times N}\rightarrow P \right.},{{{SLOPE}:\left( {P,\ b,\ e} \right)} = {\left( {{\sum\limits_{{sb} = b}^{e - 1}{{x\left( {sb} \right)}{P({sb})}}} - {\frac{1}{e - b}{\sum\limits_{{sb} = b}^{e - 1}{{x\left( {sb} \right)}{\sum\limits_{{sb} = b}^{e - 1}{P\left( {sb} \right)}}}}}} \right)\left( {{\sum\limits_{{sb} = b}^{e - 1}{x\left( {sb} \right)}^{2}} - {\frac{1}{e - b}\left( {\sum\limits_{{sb} = b}^{e - 1}{x\left( {sb} \right)}} \right)^{2}}} \right)^{- 1}}},$

where n is the actual TCX window length and x the bin number.

5.3.3.2.11.1.10. The tonal-to-noise ratio function TNR Let P∈P^(n) bethe TCX power spectrum as calculated according to subclause5.3.3.2.11.1.2 and b the start line and e the stop line of thetonal-to-noise ratio measurement range.

The TNR function, applied with IGF, is defined with:

${{TNR}:\left. {P^{n} \times N \times N}\rightarrow P \right.},{{{TNR}\left( {P,b,\ e} \right)} = {20*{\log_{10}\left( {\underset{{P_{norm}({sb})} > {1 + {adap}}}{\sum\limits_{{sb} = b}^{e - 1}}{{P_{norm}({sb})}\left( \ {\underset{{P_{norm}({sb})} < 1}{\sum\limits_{{sb} = b}^{e - 1}}\ {P_{norm}({sb})}} \right)^{- 1}}} \right)}}},$

where n is the actual TCX window length, P_(norm)(sb) is defined with

${P_{norm}\left( {sb} \right)} = {\sqrt{P\left( {sb} \right)}\left( {\frac{1}{e - b}{\sum\limits_{i = b}^{e - 1}\sqrt{P_{i}}}} \right)^{- 1}}$

and adap is defined with

${adap} = {\frac{e - b}{40}.}$

Damping:

For the IGF damping factor calculation 6 static arrays (prevTargetFIR,prevSrcFIR, prevTargetIIR and prevSrcIIR for the SFM calculation intarget and source range as well as prevDamp and dampSmooth), all of sizen8 are needed to hold filter-states over frames. Additionally a staticflag was Transient is needed to save the information of the input flagis Transient from the previous frame.

Resetting Filter States

The vectors prevTargetFIR, prevSrcFIR, prevTargetIIR, prevSrcIIR, andprevDamp and dampSmooth are all static arrays of size n8 in the IGFmodule and are initialized as follows:

${{{for}k} = 0},1,\ldots,{{nB} - {1\left\{ \begin{matrix}{{{prevTargetFIR}(k)}:=0} \\{{{preSrcFIR}(k)}:=0} \\{{{prevTargetIIR}(k)}:=0} \\{{{prevSrcFIR}(k)}:=0} \\{{{prevDamp}(k)}:={- 1}} \\{{{dampSmooth}(k)}:=2}\end{matrix} \right.}}$

This initialization shall be done

-   -   With codec start up    -   With any bitrate switch    -   With any codec type switch    -   With transition from CELP to TCX, e.g. isCelpToTCX=true    -   If the current frame has transient properties, e.g.        isTransient=true    -   If the TCX power spectrum P is not available

Calculation of Damping Factor

If the TCX power spectrum P is available and is Transient is false,calculate

${{{{tmpTarget}(k)}:=\frac{{SFM}\left( {P,{t(k)},{t\left( {k + 1} \right)}} \right)}{{CREST}\left( {P,{t(k)},{t\left( {k + 1} \right)}} \right)}},{k = 0},1,\ldots,{{nB} - 1}}{and}$${{{tmpSrc}(k)}:=\frac{{SFM}\left( {P,{m\left( {t(k)} \right)},{m\left( {t\left( {k + 1} \right)} \right)}} \right)}{{CREST}\left( {P,{m\left( {t(k)} \right)},{m\left( {t\left( {k + 1} \right)} \right)}} \right)}},{k = 0},1,\ldots,{{nB} - 1},$

where t(0), 41), . . . , t(nB) shall be already mapped with the functiontF, see subclause 5.3.3.2.11.1.1, m: N→N is the mapping function whichmaps the IGF target range into the IGF source range described insubclause 5.3.3.2.11.1.8 and n8 are the number of scale factor bands,see table 94. SFM is a spectral flatness measurement function, describedin in subclause 5.3.3.2.11.1.3 and CREST is a crest-factor functiondescribed in subclause 5.3.3.2.11.1.4.

If isCelpToTCX is true or was Transient is true, set

${{{for}{}k} = 0},1,\ldots,{{nB} - {1\left\{ \begin{matrix}{{{prevTargetFIR}(k)}:={{tmpTarget}(k)}} \\{{{preSrcFIR}(k)}:={{tmpSrc}(k)}} \\{{{prevTargetIIR}(k)}:={{tmpTarget}(k)}} \\{{{prevSrcFIR}(k)}:={{tmpSrc}(k)}}\end{matrix} \right.}}$

Calculate:

sTarget(k):=min(2.7,tmp(k)+prevTargetFIR(k)+½prevTargetIIR(k)),k=0,1, .. . ,nB−1

and

sSrc(k):=min(2.7,tmp(k)+prevSrcFIR(k)+½prevSrcIIR(k)),k=0,1, . . .,nB−1.

With these vectors calculate:

diffSFM(k):=sSrc(k)−sTarget(k),k=0,1, . . . ,nB−1.

If for k=0,1, . . . , nB−1

diffSFM(k)≤0,

or

sTarget(k)>0.1,

set

prevDamp(k):=−1

dampSmooth(k):=1

else calculate the spectral tilt with the function SLOPE, described insubclause 5.3.3.2.11.1.9:

tilt(k):=SLOPE(P,t(k),t(k+1)),k=0,1, . . . ,nB−1.

If for k=0,1, . . . , nB−1

tilt(k)<−threshTilt

or else if

tilt(k)>threshTilt and k<nB−1,

where threshTilt is defined as

${{threshTilt}:=\frac{60}{{t\left( {k + 1} \right)} - {t(k)}}},$

calculate the SFM on a shifted spectrum:

${{sShift}(k)}:=\frac{{SFM}\left( {P,{{t(k)} + {shift}},{{t\left( {k + 1} \right)} + {shift}}} \right)}{{CREST}\left( {P,{{t(k)} + {shift}},{{t\left( {k + 1} \right)} + {shift}}} \right)}$

with shift defined as

${shift}:={\frac{{sgn}\left( {{tilt}(k)} \right)}{2}{\left( {{t\left( {k + 1} \right)} - {t(k)}} \right).}}$

If

−threshTilt≤tilt(k)≤threshTilt

set

sShift(k):=0.

If for k=0,1, . . . , nB−1

sShift(k)>0.04

set the damping factor of the current frame dampCurr to zero in band k:

dampCurr(k):=0.

Otherwise, calculate dampCurr(k) as follows:

${{{dampCurr}(k)}:={e^{{{alpha}(k)}{\ln(\frac{{sTarg}{{et}(k)}}{{sSource}(k)})}} + {{beta}(k)}}},$

where alpha is defined as

${{alpha}(k)}:={\min\left( {\frac{320}{t\left( {k + 1} \right)},1.25} \right)}$

and beta is defined as

${{beta}(k)}:=\left\{ {\begin{matrix}{{10 + {adap} - {{TNR}\left( {P,{t(k)},{t\left( {k + 1} \right)}} \right)}},} & {{10 + {adap} - {{TNR}\left( {P,{t(k)},{t\left( {k + 1} \right)}} \right)}} > 0} \\{0,} & {else}\end{matrix},} \right.$

where TNR is the tonal-to-noise ratio function as described in subclause5.3.3.2.11.1.10 and adap is defined as

${adap}:={\frac{{t\left( {k + 1} \right)} - {t(k)}}{40}.}$

If for k=0,1, . . . , nB−1

prevDamp(k)=−1,

set

prevDamp(k):=max(currDamp(k),0.1).

Calculate the vector of damping factors d of size nB:

d(k):=min(½(currDamp(k)+prevDamp(k))+0.1*dampSmooth(k),1).

Finally, if is Transient is false and the power spectrum P is available,update the filters

${{{for}{}k} = 0},1,\ldots,{{nB} - {1\left\{ \begin{matrix}{{{prevTargetFIR}(k)}:={{tmpTarget}(k)}} \\{{{preSrcFIR}(k)}:={{tmpSrc}(k)}} \\{{{prevTargetIIR}(k)}:={{sTarget}(k)}} \\{{{prevSrcIIR}(k)}:={{sSrc}(k)}}\end{matrix} \right.}}$

The names of the values/indices/parameters in the preceding portion aresimilar to the corresponding parameters/indices/values that have beendiscussed throughout this specification. Subsequently, several resultsfrom listening tests are discussed in the context of FIGS. 11 a to 11 c.

These listening tests were conducted showing the benefit of damping bycomparing items that were coded with enabled damping against items thatwere coded without.

The first result illustrated in FIG. 11 a is an a-B-comparison-test at abit rate of 13.2 kbps and a sample rate of 32 kHz using mono-items. Theresults are shown in FIG. 11 a showing the a-B-test damping versus nodamping at 13.2 kbps.

The second one illustrated in FIG. 11 b was a MUSHRA-test at 24.4 kbpsand a sample rate of 32 kHz using mono-items. Here, two versions withoutdamping were compared to the new version with damping. The results areshown in FIG. 11 b (absolute scores) and FIG. 11 c (difference scores).

The inventively encoded audio signal can be stored on a digital storagemedium or a non-transitory storage medium or can be transmitted on atransmission medium such as a wireless transmission medium or a wiredtransmission medium such as the Internet.

Although some aspects have been described in the context of anapparatus, it is clear that these aspects also represent a descriptionof the corresponding method, where a block or device corresponds to amethod step or a feature of a method step. Analogously, aspectsdescribed in the context of a method step also represent a descriptionof a corresponding block or item or feature of a correspondingapparatus.

Depending on certain implementation requirements, embodiments of theinvention can be implemented in hardware or in software. Theimplementation can be performed using a digital storage medium, forexample a floppy disk, a DVD, a CD, a ROM, a PROM, an EPROM, an EEPROMor a FLASH memory, having electronically readable control signals storedthereon, which cooperate (or are capable of cooperating) with aprogrammable computer system such that the respective method isperformed.

Some embodiments according to the invention comprise a data carrierhaving electronically readable control signals, which are capable ofcooperating with a programmable computer system, such that one of themethods described herein is performed.

Generally, embodiments of the present invention can be implemented as acomputer program product with a program code, the program code beingoperative for performing one of the methods when the computer programproduct runs on a computer. The program code may for example be storedon a machine readable carrier.

Other embodiments comprise the computer program for performing one ofthe methods described herein, stored on a machine readable carrier or anon-transitory storage medium.

In other words, an embodiment of the inventive method is, therefore, acomputer program having a program code for performing one of the methodsdescribed herein, when the computer program runs on a computer.

A further embodiment of the inventive methods is, therefore, a datacarrier (or a digital storage medium, or a computer-readable medium)comprising, recorded thereon, the computer program for performing one ofthe methods described herein.

A further embodiment of the inventive method is, therefore, a datastream or a sequence of signals representing the computer program forperforming one of the methods described herein. The data stream or thesequence of signals may for example be configured to be transferred viaa data communication connection, for example via the Internet.

A further embodiment comprises a processing means, for example acomputer, or a programmable logic device, configured to or adapted toperform one of the methods described herein.

A further embodiment comprises a computer having installed thereon thecomputer program for performing one of the methods described herein.

In some embodiments, a programmable logic device (for example a fieldprogrammable gate array) may be used to perform some or all of thefunctionalities of the methods described herein. In some embodiments, afield programmable gate array may cooperate with a microprocessor inorder to perform one of the methods described herein. Generally, themethods may be performed by any hardware apparatus.

While this invention has been described in terms of several embodiments,there are alterations, permutations, and equivalents which fall withinthe scope of this invention. It should also be noted that there are manyalternative ways of implementing the methods and compositions of thepresent invention. It is therefore intended that the following appendedclaims be interpreted as including all such alterations, permutationsand equivalents as fall within the true spirit and scope of the presentinvention.

1. An apparatus for encoding an audio signal, comprising: a core encoderfor core encoding first audio data in a first spectral band; aparametric coder for parametrically coding second audio data in a secondspectral band being different from the first spectral band, wherein theparametric coder comprises: an analyzer for analyzing the first audiodata in the first spectral band to acquire a first analysis result andfor analyzing the second audio data in the second spectral band toacquire a second analysis result; a compensator for calculating acompensation value using the first analysis result and the secondanalysis result; and a parameter calculator for calculating a parameterfrom the second audio data in the second spectral band using thecompensation value.
 2. The apparatus of claim 1, wherein the analyzer isconfigured to calculate, as the first analysis result, a firstquantitative value, and as the second analysis result, a secondquantitative value, wherein the compensator is configured to calculate aquantitative compensation value from the first quantitative value andfrom the second quantitative value, and wherein the parameter calculatoris configured for calculating a quantitative parameter using thequantitative compensation value.
 3. The apparatus of claim 1, whereinthe analyzer is configured to analyze a first characteristic of thefirst audio data to acquire the first analysis result, and to analyzethe same first characteristic of the second audio data in the secondspectral band to acquire the second analysis result, and wherein theparameter calculator is configured for calculating the parameter fromthe second audio data in the second spectral band by evaluating a secondcharacteristic, the second characteristic being different from the firstcharacteristic.
 4. The apparatus of claim 3, wherein the firstcharacteristic is a spectral fine structure characteristic or an energydistribution characteristic within the first spectral band, or whereinthe second characteristic is an envelope measure or an energy relatedmeasure or a power related measure of spectral values within the secondspectral band.
 5. The apparatus of claim 1, wherein the first spectralband and the second spectral band are mutually exclusive to each other,wherein the analyzer is configured to calculate the first analysisresult without using the second audio data in the second spectral band,and to calculate the second analysis result without using the firstaudio data in the first spectral band.
 6. The apparatus of claim 1,wherein the audio signal comprises a time sequence of frames, whereinthe compensator is configured to calculate a current compensation valuefor a current frame using a previous compensation value for a previousframe.
 7. The apparatus of claim 1, wherein the parametric coder isconfigured for parametrically coding third audio data in a thirdspectral band, wherein the third spectral band comprises higherfrequencies than the second spectral band, and wherein the compensatoris configured to use a third weighting value in calculating acompensation value for the third spectral band, wherein the thirdweighting value is different from a second weighting value used forcalculating a compensation value for the second spectral band.
 8. Theapparatus of claim 1, wherein the analyzer is configured to additionallycalculate a tonal-to-noise ratio of the second audio data in the secondspectral band, and wherein the compensator is configured to calculatethe compensation value dependent on the tonal-to-noise ratio of thesecond audio data so that a first compensation value is acquired for afirst tonal-to-noise ratio or a second compensation value is acquiredfor a second tonal-to-noise ratio, the first compensation value beinggreater than the second compensation value, and the first tonal-to-noiseratio being greater than the second tonal-to-noise ratio
 9. Theapparatus of claim 1, wherein the parameter calculator is configured forcalculating a non-compensated parameter from the second audio data andfor combining the non-compensated parameter and the compensation valueto acquire the parameter.
 10. The apparatus of claim 1, furthercomprising an output interface for outputting core-encoded audio data inthe first spectral band and the parameter.
 11. The apparatus of claim 1,wherein the compensator is configured to determine the compensationvalue by applying a psychoacoustic model, wherein the psychoacousticmodel is configured to evaluate a psychoacoustic mismatch between thefirst audio data and the second audio data using the first analysisresult and the second analysis result to acquire the compensation value.12. The apparatus of claim 1, wherein the audio signal comprises atime-sequence of frames, and wherein the analyzer is configured foranalyzing first audio data in the first spectral band of a frame toacquire the first analysis result and for analyzing second audio data ofthe frame in the second spectral band to acquire a second analysisresult for the frame, wherein the compensator is configured forcalculating a compensation value for the frame using the first analysisresult for the frame and the second analysis result for the frame; andwherein the parameter calculator is configured for calculating theparameter from the second audio data in the second spectral band of theframe using the compensation value for the frame, or wherein theparametric coder further comprises: a compensation detector fordetecting, based on the first analysis result and the second analysisresult, whether the parameter for the second spectral band of a frame isto be calculated either using the compensation value in a compensationsituation or in a non-compensation situation.
 13. The apparatus of claim1, wherein a compensation detector is configured to detect acompensation situation, when a difference between the first analysisresult and the second analysis result comprises a predeterminedcharacteristic, or when the second analysis result comprises apredetermined characteristic, wherein the compensation detector isconfigured to detect that a spectral band is not to be compensated, whena power spectrum is not available to the audio encoder or when a currentframe is detected to be a transient frame, or wherein the compensator isconfigured to calculate the compensation value based on a quotient ofthe first analysis result and the second analysis result.
 14. Theapparatus of claim 1, wherein the analyzer is configured to calculate aspectral flatness measure, a crest factor or a quotient of the spectralflatness measure and the crest factor for the first spectral band as thefirst analysis result, and to calculate a spectral flatness measure or acrest factor or a quotient of the spectral flatness measure and thecrest factor for the second spectral band as the second analysis result,or wherein the parameter calculator is configured to calculate, from thesecond audio data, a spectral envelope information or a gain factor, orwherein the compensator is configured to calculate the compensationvalue so that, for a first difference between the first analysis resultand the second analysis result, a first compensation value is acquired,and for a second difference between the first analysis result and thesecond analysis result, a second compensation value is calculated,wherein the first difference is greater than the second difference, andwherein the first compensation value is greater than the secondcompensation value.
 15. The apparatus of claim 14, wherein the analyzeris configured to calculate a spectral tilt from the second audio data,wherein the analyzer is configured to examine whether there is a tonalcomponent close to a border of the second spectral band, and wherein acompensation detector of the parametric coder is configured to determinethat the parameter is to be calculated using the compensation value onlywhen the spectral tilt is below a predetermined threshold, or when thespectral tilt is above a predetermined threshold and the examination hasdetermined that there exists a tonal component close to the border. 16.The apparatus of claim 1, further comprising: a decoder for decodingencoded first audio data in the first spectral band to acquire encodedand decoded first audio data, wherein the analyzer is configured tocalculate the first analysis result using the encoded and decoded firstaudio data, and to calculate the second analysis result from the secondaudio data from the audio signal input into the apparatus for encoding.17. The apparatus of claim 1, further comprising: a patch simulator forsimulating a patching result for the second spectral band, the patchingresult comprising at least one spectral line from the second spectralband included in a core encoded audio signal; wherein the analyzer isconfigured to calculate the first analysis result using the first audiodata and the at least one spectral line from the second spectral band;and to calculate the second analysis result from the second audio datafrom the audio signal input into the apparatus for encoding.
 18. Theapparatus of claim 1, wherein the core encoder is configured to encodethe first audio data in a sequence of real valued spectra, wherein theanalyzer is configured to calculate the first and the second analysisresult from a sequence of power spectra, wherein a power spectrum iscalculated from the audio signal input into the apparatus for encodingor is derived from a real valued spectrum used by the core encoder. 19.The apparatus of claim 1, wherein the core encoder is configured to coreencode the audio signal at least in a core band extending until anenhancement start frequency, wherein the core band comprises the firstspectral band and at least one further source band overlapping with thefirst spectral band, wherein the audio signal comprises an enhancementrange extending from the enhancement start frequency until a maximumfrequency, wherein the second spectral band and at least one furthertarget band are included in the enhancement range, wherein the secondspectral band and the further target band do not overlap with eachother.
 20. The apparatus of claim 19, wherein the enhancement startfrequency is a cross-over frequency and a core encoded signal is bandlimited to the cross-over frequency, or wherein the enhancement startfrequency is an intelligent gap filling start frequency and a coreencoded signal is band-limited to the maximum frequency being greaterthan the enhancement start frequency.
 21. The apparatus of claim 1,wherein the parameter calculator is configured to calculate a gainfactor for the second spectral band based on the second audio data inthe second spectral band, to calculate a damping factor as thecompensation value, and to multiply the gain factor for the band by thedamping factor to acquire a compensated gain factor as the parameter,and wherein the apparatus further comprises an output interface foroutputting core-encoded audio data in the first spectral band and thecompensated gain factor as the parameter.
 22. A method of encoding anaudio signal, comprising: core encoding first audio data in a firstspectral band; parametrically coding second audio data in a secondspectral band being different from the first spectral band, wherein theparametrically coding comprises: analyzing the first audio data in thefirst spectral band to acquire a first analysis result and analyzing thesecond audio data in the second spectral band to acquire a secondanalysis result; calculating a compensation value using the firstanalysis result and the second analysis result; and calculating aparameter from the second audio data in the second spectral band usingthe compensation value, wherein the analyzing comprises calculating atonal-to-noise ratio of the second audio data in the second spectralband, and wherein the calculating the compensation value comprisescalculating the compensation value dependent on the tonal-to-noise ratioof the second audio data so that a first compensation value is acquiredfor a first tonal-to-noise ratio or a second compensation value isacquired for a second tonal-to-noise ratio, the first compensation valuebeing greater than the second compensation value, and the firsttonal-to-noise ratio being greater than the second tonal-to-noise ratio.23. A system for processing an audio signal, comprising: an apparatusfor encoding an audio signal of claim 1; and a decoder for receiving anencoded audio signal comprising encoded first audio data in the firstspectral band and a parameter representing second audio data in thesecond spectral band, wherein the decoder is configured for performing aspectral enhancement operation in order to regenerate synthesized audiodata for the second spectral band using the parameter and decoded firstaudio data in the first spectral band.
 24. A method of processing anaudio signal, comprising: encoding an audio signal, comprising: coreencoding first audio data in a first spectral band; parametricallycoding second audio data in a second spectral band being different fromthe first spectral band, wherein the parametrically coding comprises:analyzing the first audio data in the first spectral band to acquire afirst analysis result and analyzing the second audio data in the secondspectral band to acquire a second analysis result; calculating acompensation value using the first analysis result and the secondanalysis result; and calculating a parameter from the second audio datain the second spectral band using the compensation value, wherein theanalyzing comprises calculating a tonal-to-noise ratio of the secondaudio data in the second spectral band, and wherein the calculating thecompensation value comprises calculating the compensation valuedependent on the tonal-to-noise ratio of the second audio data so that afirst compensation value is acquired for a first tonal-to-noise ratio ora second compensation value is acquired for a second tonal-to-noiseratio, the first compensation value being greater than the secondcompensation value, and the first tonal-to-noise ratio being greaterthan the second tonal-to-noise ratio; receiving an encoded audio signalcomprising encoded first audio data in the first spectral band and aparameter representing second audio data in the second spectral band;and performing a spectral enhancement operation in order to regeneratesynthesized audio data for the second spectral band using the parameterand decoded first audio data in the first spectral band.
 25. Anon-transitory digital storage medium having computer-readable codestored thereon to perform a method of encoding an audio signal,comprising: core encoding first audio data in a first spectral band;parametrically coding second audio data in a second spectral band beingdifferent from the first spectral band, wherein the parametricallycoding comprises: analyzing the first audio data in the first spectralband to acquire a first analysis result and analyzing the second audiodata in the second spectral band to acquire a second analysis result;calculating a compensation value using the first analysis result and thesecond analysis result; and calculating a parameter from the secondaudio data in the second spectral band using the compensation value,wherein the analyzing comprises calculating a tonal-to-noise ratio ofthe second audio data in the second spectral band, and wherein thecalculating the compensation value comprises calculating thecompensation value dependent on the tonal-to-noise ratio of the secondaudio data so that a first compensation value is acquired for a firsttonal-to-noise ratio or a second compensation value is acquired for asecond tonal-to-noise ratio, the first compensation value being greaterthan the second compensation value, and the first tonal-to-noise ratiobeing greater than the second tonal-to-noise ratio, when thecomputer-readable code is run by a computer.
 26. A non-transitorydigital storage medium having computer-readable code stored thereon toperform a method of processing an audio signal, comprising: encoding anaudio signal, comprising: core encoding first audio data in a firstspectral band; parametrically coding second audio data in a secondspectral band being different from the first spectral band, wherein theparametrically coding comprises: analyzing the first audio data in thefirst spectral band to acquire a first analysis result and analyzing thesecond audio data in the second spectral band to acquire a secondanalysis result; calculating a compensation value using the firstanalysis result and the second analysis result; and calculating aparameter from the second audio data in the second spectral band usingthe compensation value, wherein the analyzing comprises calculating atonal-to-noise ratio of the second audio data in the second spectralband, and wherein the calculating the compensation value comprisescalculating the compensation value dependent on the tonal-to-noise ratioof the second audio data so that a first compensation value is acquiredfor a first tonal-to-noise ratio or a second compensation value isacquired for a second tonal-to-noise ratio, the first compensation valuebeing greater than the second compensation value, and the firsttonal-to-noise ratio being greater than the second tonal-to-noise ratio;receiving an encoded audio signal comprising encoded first audio data inthe first spectral band and a parameter representing second audio datain the second spectral band; and performing a spectral enhancementoperation in order to regenerate synthesized audio data for the secondspectral band using the parameter and decoded first audio data in thefirst spectral band, when the computer-readable code is run by acomputer.